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SEKE 2012 Proceedings - Knowledge Systems Institute
SEKE 2012 Proceedings - Knowledge Systems Institute
SEKE 2012 Proceedings - Knowledge Systems Institute
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A model introducing SOAs quality attributes decomposition Riad Belkhatir, Mourad Oussalah Department of Computing University of Nantes Nantes, France {riad.belkhatir, mourad.oussalah}@univ-nantes.fr Arnaud Viguier Department Research and Development BeOtic Rezé, France arnaud.viguier@beotic.com Abstract—Recently, service oriented architecture (SOA) has been popularized with the emergence of standards like Web services. Nevertheless, the shift to this architectural paradigm could potentially involve significant risks including projects abandonments. With this in mind, the question of evaluating SOA quality arose. The appearance of methods like ATAM or SAAM propelled software architecture evaluation to a standard stage for any paradigm. However, there still are a number of concerns that have been raised with these methods; in particular their cost in terms of time and money, essentially because of the hand-operated nature of the evaluations conducted. The model proposed in this paper for evaluating SOAs takes as a starting point the McCall model; it allows the whole architecture to be decomposed in three types of quality attributes (factor, criterion and metric). Keywords- SOA; factor; criterion; metric I. INTRODUCTION Architectural paradigms are design patterns for the structure and the interconnection between software systems [1]. Their evolution is generally linked to the evolution of the technology. An architectural paradigm defines groups of systems in terms of: • Model of structure. • Component and connector vocabularies. • Rules or constraints on relations between systems [2]. We can distinguish a few architectural paradigms for distributed systems, and, among the most noteworthy ones, three have contributed to the evolution of the concerns. These are chronologically, object oriented architectures (OOA), component based architectures (CBA) and service oriented architectures (SOA). First developers were quickly aware of code repetitions in applications and sought to define mechanisms limiting these repetitions. OOA is focused on this concern and its development is one of the achievements of this research. OOA provides great control of the reusability (reusing a system the same way or through a certain number of modifications) which paved the way to applications more and more complex and consequently to the identification of new limits in terms of granularity. These limits have led to the shift of the concerns towards the composability (combining in a sure way its architectural elements in order to build new systems or composite architectural elements). Correlatively, the software engineering community developed and introduced CBA to overcome this new challenge and thus, the CBA reinforces control of the composability and clearly formalizes the associated processes. By extension, this formalization establishes the base necessary to a utomation possibilities. At the same time, a part of the software community took the research in a n ew direction: the dynamism concern (developing applications able to adapt in a dynamic, automatic and autonomous ways their behaviors to answer the changing needs of requirements and contexts as well as possibilities of errors) as the predominant aspect. In short, SOA has been developed on the basis of the experience gained by objects and components, with a focalization from the outset on ways of improving the dynamism. Service oriented architecture is a popular architectural paradigm aiming to model and to design distributed systems [3]. SOA solutions were created to satisfy commercial objectives. This refers to a s uccessful integration of existing systems, the creation of innovating services for customers and cost cutting while remaining competitive. For the purpose of making a system robust, it is necessary that its architecture can meet the functional requirements ("what a system is supposed to do"; defining specific behaviors or functions) and the nonfunctional ones ("what a system is supposed to be"; in other words, the quality attributes) [4]. Furthermore, developing an SOA involves many risks, so much the complexity of this technology is notable (particularly for services orchestration). First and foremost among these, is the risk of not being able to answer favorably to expectations in terms of quality of services because quality attributes directly derive from business objectives. Multi-million dollar projects, undertaken by major enterprises (Ford, GSA) failed and were abandoned. As these risks are distributed through all the services, the question of evaluating SOA has recently arisen. It is essential to carry out the evaluation of the a rchitecture relatively early in the software lifecycle to save time and money [5]. This is to identify and correct remaining errors that might have occurred after the software design stage and, implicitly, to reduce subsequent risks. Lots of tools have been created to e valuate SOAs but none of them clearly demonstrated its effectiveness 324
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SEKE San Francisco Bay July 1-3 201
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Copyright © 2012 by Knowledge Syst
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The 24 th International Conference
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Zhenyu Chen, Nanjing University, Ch
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Riccardo Martoglia, University of M
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Poster/Demo Sessions Co-Chairs Fars
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Evaluating the Cost-Effectiveness o
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Program Understanding Evaluating Op
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An Empirical Study of Execution-Dat
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Computer Forensics: Toward the Cons
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Modeling Bridging KDM and ASTM for
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A Mapping Study on Software Product
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A proposal for the improvement of t
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The rest of this paper is orga nize
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Figure 1. An example to illustrate
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Figure 2. Sequence Diagram of Train
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test, we did not find any significa
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the model checkers SPIN [8] and NuS
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Data Set TABLE II. DATA SETS Artifa
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Take basic requirements from user a
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diagram could give developers an in
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Figure 2. Overview of the RSLingo a
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DETECTING EMERGENT BEHAVIOR IN DIST
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Stability of Filter-Based Feature S
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Algorithm 1: Threshold-Based Featur
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Cloud Application Resource Mapping
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TABLE I SOFTWARE DATASETS CHARACTER
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1) Classifiers: In this study, soft
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Progressive Clustering with Learned
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IV. DATA SOURCES We have been worki
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meta-data we assign to indicate sig
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Multi-Objective Optimization of Fuz
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VI. EXPERIMENTAL RESULTS The presen
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Generating Performance Test Scripts
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test duration(s) for the scenario(s
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which are composed by the name and
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A Catalog of Patterns for Concept L
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assisted solution for lattice analy
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The complete lattice of the class s
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Client-Side Rendering Mechanism: A
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JavaScript code directly within the
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Fig. 6. CPU usage percentage of pre
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One of the st udents from Group B t
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4 Model Checking DPN We use HyTech
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Recommender systems are usually cla
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properties. In particular, the foll
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Conference Dataset Anatomy Dataset
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Online Anomaly Detection for Compon
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Figure 1. Mindmap of Reuse Design P
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subject also caused outliers for re
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Online Probability Application Char
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TABLE II THE PARAMETERS FOR THE HAR
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Section 5 d iscusses some related w
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model and the analysis results. The
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Algorithm 2 MarkStatements function
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Gupta extended HGS and proposed the
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Evolutionary Learning and Fuzzy Log
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In addition to the rules, the knowl
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As described in the previous sectio
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TABLE IX. USING SVM FOR LEARNING tr
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eventually triggers a co mmon task.
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Input: A resource oriented workflow
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access control exists, the action i
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ICrudSchema and shown in Figure 3.
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Connectors for Secure Software Arch
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Non-repudiation security service pr
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anAsynchronousCustomer InterfaceCon
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How Social Network APIs Have Ended
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OSN Social Feed Unique Features Con
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users can control the reach of thei
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Computer Forensics: Toward the Cons
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In 2009, Cohen et al. in [4] have o
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Figure 1. Figure 1 shows an overvie
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Pointcut Design with AODL Saqib iqb
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system attributes, methods and exec
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Feature modeling and Verification b
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I2Sim simulation model was transfor
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Automatic Generation of Architectur
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we dealt w ith the verticals rules.
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different from replacing it, we dec
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which the airport data did not cont
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classified. Recall is the probabili
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Testing Interoperability Security P
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k v ( df i ) 0 , it means that the
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Model & Method Feasibility Evaluati
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Structural Testing for Multithreade
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derivation dependencies. The third
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model extension as proposed in [6].
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Figure 1. The process for engineeri
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way to detect something which could
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obtain the input of experts on desi
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These latter would be clustered acc
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DC2AP Element and their Application
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Adaptive software should basically
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Visual Studio Achievements, a Visua
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the project. This achievement has t
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FTS is an important research area,
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C. Dependent Variables and Measures
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D. Conclusion Validity Conclusion v
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evaluation of team productivity, qu
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Using the Results from a Systematic
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Identification Guidelines for the D
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Empirical Validation of Variability
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contribution of each study was made
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descriptions must also b e configur
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A Variability Management Method for
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Reconfiguration of Robot Applicatio
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machine may be empty which should l
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software, based on revised requirem
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A Process-Based Approach to Improvi
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Appropriate processes m ust support
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Automatic Acquisition of isA Relati
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Match production rules Enterprise S
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shown at Figure 5. Objectives are s
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Rendering UML Activity Diagrams as
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a = O1 → a → O2 b = O2 → b
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umlTUowl - A Both Generic and Vendo
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The tool’s ability to deal with S
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Elem. UML Example D 12 Harmonizing
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4) Associations: In the first test
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III. GRAPH REPRESENTATION OF CLASS
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as an add-in to popular UML m odeli
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742
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744
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746
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her necessities. However, the progr
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Figure 3. Global Log. of terms. The
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two stages. The first stage is focu
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754
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756
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758
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With the GDUC approach, we can mode
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Figure 6. Three proposals containin
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764
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766
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Proactive Two Way Mobile Advertisem
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information. If more than one adver
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Users can al so publish adv ertisem
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The COIN Platform: Supporting the M
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A-3
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Checking Contracts for AOP using XP
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Maicon B. da Silveira, 112 Aldo Dag
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Seyedehmehrnaz Mireslami, 70 Takao
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Wei Zhang, 422 Wenbo Zhang, 188 Zhi
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Desmond Greer Eric Gregoire Christi
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Poster/Demo Presenter’s Index A A
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